We compared our results for performing multi-frame interpolation with a state-of-the-art approach, SepConv [1]}. We present results comparing 3-frame interpolation in Fig. REF . We convert our grayscale testing images to 3 channels (RGB) before applying the SepConv interpolation algorithm. Although the results from SepConv provide better visual experience, they have salient artifacts around large motion regions. Note that performing intensity only frame interpolation produces significant artifacts in the presence of severe occlusions. On the other hand, our event-driven frame interpolation is able to successfully recover image details in occluded regions of interpolated framesPlease see videos of results in supplementary material.. For a quantitive comparison, the SepConv method has an average SSIM of 0.9566 and PSNR of 29.79. Ours have average SSIM of 0.9741 and PSNR of 37.64.
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